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these new noise sources, influenced by complex building structures and in the presence of other noise sources, is limited, and scientific studies to understand the impact on people are therefore needed
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into useful chemical products is at the heart of the Net Zero transition. In liquid-phase heterogeneous systems, controlling which product forms and understanding why it forms remain one of the field's most
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Application deadline: 21 May 2026 Apply now Today’s social media platforms are actors with a complex stake in shaping knowledge about global crises like climate change. Recent developments even reflect
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Python and/or R for bioinformatics and ability to write clean, reproducible, and well-documented code for complex multi-step pipelines. have documented experience from cancer research. Additional
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs
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the German tradition (e.g., Kant, Humboldt, Goethe) 3. Its complex reception in Germany and beyond 4. Its contemporary relevance for environmental studies and scientific discourse Project activities include
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areas, which will be used to train and assess boundary layer neural network models. The student will develop and evaluate suitable ML architectures, analysing the trade-offs between different modelling
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 18 days ago
ABHSSYS (Acoustic Black Holes for Silent SYStems, Grant agreement ID: 101227712) is a European Doctoral Network funded by the Marie Skłodowska-Curie Actions (MSCA), dedicated to advancing innovative
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing